code: def test_max_score_1():
      def objective_function(para):
          score = -para["x1"] * para["x1"]
          time.sleep(0.01)
          return score
  
      search_space = {
          "x1": list(np.arange(0, 100, 0.1)),
      }
  
      max_score = -9999
  
      c_time = time.perf_counter()
      hyper = Hyperactive()
      hyper.add_search(
          objective_function,
          search_space,
          n_iter=100000,
          initialize={"warm_start": [{"x1": 99}]},
          max_score=max_score,
      )
      hyper.run()
      diff_time = time.perf_counter() - c_time
  
      print(
          "\n Results head \n",
          hyper.search_data(objective_function).head(),
      )
      print(
          "\n Results tail \n",
          hyper.search_data(objective_function).tail(),
      )
  
      print("\nN iter:", len(hyper.search_data(objective_function)))
  
      assert diff_time < 1
  
file_path: Hyperactive/tests/test_max_score.py
imports: import time
  import numpy
  from sklearn.datasets import load_breast_cancer
  from sklearn.model_selection import cross_val_score
  from sklearn.tree import DecisionTreeClassifier
  from hyperactive import Hyperactive
  from hyperactive.optimizers import RandomSearchOptimizer, HillClimbingOptimizer
label_desc: Use image node_id 3 for calling a global function with example usage: test_max_score_1() and returns: score